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        Download the raw data used to create the plots in this report below:

        Note that additional data was saved in multiqc_data when this report was generated.

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        If you use plots from MultiQC in a publication or presentation, please cite:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

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        Tool Citations

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        To help with this, you can download publication details of the tools mentioned in this report:

        About MultiQC

        This report was generated using MultiQC, version 1.25.1

        You can see a YouTube video describing how to use MultiQC reports here: https://youtu.be/qPbIlO_KWN0

        For more information about MultiQC, including other videos and extensive documentation, please visit http://multiqc.info

        You can report bugs, suggest improvements and find the source code for MultiQC on GitHub: https://github.com/MultiQC/MultiQC

        MultiQC is published in Bioinformatics:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

        A modular tool to aggregate results from bioinformatics analyses across many samples into a single report.

        Report generated on 2024-10-23, 21:13 CST based on data in: /scratch/home/dperez/resultados/VCS_p/out

        General Statistics

        Showing 0/2 rows and 3/3 columns.
        Sample NameChange rateTs/TvM Variants
        P1Tumor_snpEff_stats
        0
        0.000
        0.00M
        P2Tumor_snpEff_stats
        0
        0.000
        0.00M

        SnpEff

        Version: 5.2c

        Annotates and predicts the effects of variants on genes (such as amino acid changes).URL: http://snpeff.sourceforge.netDOI: 10.4161/fly.19695

        Variants by Genomic Region

        The stacked bar plot shows locations of detected variants in the genome and the number of variants for each location.

        The upstream and downstream interval size to detect these genomic regions is 5000bp by default.

        Created with MultiQC

        Variant Effects by Impact

        The stacked bar plot shows the putative impact of detected variants and the number of variants for each impact.

        There are four levels of impacts predicted by SnpEff:

        • High: High impact (like stop codon)
        • Moderate: Middle impact (like same type of amino acid substitution)
        • Low: Low impact (ie silence mutation)
        • Modifier: No impact

        Variants by Effect Types

        The stacked bar plot shows the effect of variants at protein level and the number of variants for each effect type.

        This plot shows the effect of variants with respect to the mRNA.

        Created with MultiQC

        Variants by Functional Class

        The stacked bar plot shows the effect of variants and the number of variants for each effect type.

        This plot shows the effect of variants on the translation of the mRNA as protein. There are three possible cases:

        • Silent: The amino acid does not change.
        • Missense: The amino acid is different.
        • Nonsense: The variant generates a stop codon.

        Software Versions

        Software Versions lists versions of software tools extracted from file contents.

        SoftwareVersion
        SnpEff5.2c

        MultiQC v1.25.1 - Written by Phil Ewels, available on GitHub.

        This report uses Plotly, jQuery, jQuery UI, Bootstrap and FileSaver.js.